UUV导航测速信息的灰色自适应滤波方法研究

Research on Grey Adaptive Filtering Method of Velocity Information for UUV Navigation

针对水下无人航行器UUV(Unmanned Underwater Vehicle)的导航测速数据受海洋环境噪声影响大、处理实时性要求高的问题,提出了一种基于灰色动态预测和数据自适应融合的滤波方法。该方法考虑到UUV的速度在连续变化前提下可能存在的机动性,将基本的静态灰色预测模型改进为灰色动态预测模型,以获得速度数据的近似估计值。然后根据估计值和实际采样值之间的偏差,自适应的调整两者之间的权重系数进行融合,以实现实时的数据滤波。通过对UUV海上试验数据的验证,证明了该方法的有效性。

According to the problems of large ocean noise influence and high requirement of real-time processing forUUV navigation velocity data,a data filtering method using grey prediction and adaptive fusion is proposed in thispaper. Considering the maneuverability of UUV and continuous variability of velocity,an improved dynamic greyprediction model is used to obtain the estimated values of velocity data instead of the traditional grey model. Theweight coefficients of the fusion filtering are adjusted adaptively based on the deviation of the estimated and sam-pling values. Finally,the simulation results using UUV experiment data show that the method proposed is effective.